Aircraft Sensor Alignment Using Gyroscopic Flexure Compensation
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Solution Overview
Problem
Countermeasure systems on aircraft face challenges in precisely aligning electro-optical sensors due to the flexible nature of the aircraft, which complicates the mapping of incoming threats into a common reference frame.
Innovation Solution
An alignment system utilizing accelerometers or gyroscopes to account for aircraft flexure, incorporating a low-pass filter to eliminate body flex and improve Kalman estimator accuracy, with gyroscopes mounted on electro-optical sensors communicating with a central gyroscope within an inertial navigation system to determine relative attitudes and map threat detections into a common reference frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensors are mounted on a flexible aircraft body, then the countermeasure system can be integrated into the aircraft structure, but the sensors rotate relative to each other due to aircraft flexure making alignment difficult
Solution Approach 1:
The system dynamically compensates for aircraft flexure by continuously measuring the relative orientation between sensors and the inertial navigation system using gyroscopes and accelerometers. The alignment is not fixed but adaptively updated in real-time to account for changes in the flexible aircraft structure during flight maneuvers.
Solution Approach 2:
The system uses feedback from inertial measurement units (gyroscopes and accelerometers) mounted on both the sensors and the inertial navigation system to continuously monitor and correct for relative orientation changes. This feedback loop enables the system to maintain accurate alignment despite the flexible aircraft body causing dynamic changes in sensor positions.
2Reliability
If traditional alignment methods are used without filtering, then all motion data is preserved, but body flex frequencies contaminate the alignment measurements
Solution Approach 1:
The system extracts and removes the harmful body flex frequency components from the gyroscope and accelerometer measurements using spectral analysis and filtering techniques. By identifying and eliminating these specific frequency ranges, the system isolates the useful alignment information from the contaminating flexure data.
Solution Approach 2:
The system changes the frequency domain parameters of the motion data by applying filters that selectively attenuate body flex frequencies while preserving the lower frequency alignment information. This parameter transformation in the frequency domain enables separation of useful signal from harmful noise.
3Measurement precision
If complex filtering and estimation algorithms are applied, then alignment accuracy is improved, but computational load increases
Solution Approach 1:
The system applies filtering and estimation algorithms selectively rather than continuously. By identifying periods when alignment measurements are most critical and applying the computationally intensive Kalman filter only during those periods, the system achieves high accuracy when needed while reducing overall computational burden during normal operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables accurate and fast convergence of transfer alignment, reducing computational load and convergence time, and improves steady-state accuracy, allowing for precise alignment of sensors and effective threat detection.
Implementation Method 1
one or more gyroscopes mounted on an electro-optical sensor, which may be an infrared sensor, that is in electrical communication with a central gyroscope, which may be part of an INS
Implementation Method 2
The method can apply a filter, such as a low pass filter, to a gyroscope measurement to eliminate body flex of the platform while preserving sufficient low frequency common mode motion
Data Source
AI summary
An alignment system for sensor or other electrical device filters rate data from gyroscopes and integrates the same to determine an alignment error state that is populated into a direction cosine matrix that pre-rotates measurement from a first electrical device into an estimated coordinate frame to determine a static alignment between first and second electrical devices or sensors. The system may be part of a countermeasure system on an aircraft. A first electrical device may be an inertial navigation system (INS), and a second electrical device may be an inertial measurement unit (IMU). The attitude of the IMU is used to translate the detected threats from the countermeasure system into a common reference frame of the INS.